Data Stream Mining, i.e. the process of extracting knowledge structures from continuous, rapid data records, is becoming increasingly interesting to use in various environments, such as for instance in mobile communication systems.
There are multiple frameworks available for performing data stream mining, where S4, Storm and Spark are just a few. S4 is for instance described by Leonardo Neumeyer et al in “S4 : Distributed Stream Computing Platform”, 2010 IEEE International Conference on Data Mining Workshops.
However, all these frame works or platforms have their own Application Programming Interface (API) and programming style and therefore behave differently from each other.
A user wanting to implement an application based on a stream processing frame work that best suits his need will then have to investigate the capability of the framework him- or herself in order to determine which is most suitable and then learn the API of the chosen framework. This is both time consuming and requires considerable skills by the user.
It would therefore be of interest to simplify for a user in the selecting of an appropriate stream processing framework and implementing an application using the selected stream processing framework.